1. Field of the Invention
The present invention relates to a color variation specification method, restricted color determination method, and restricted color determination device which are used when a digitized natural image is displayed on a color display device which is capable of simultaneously displaying only a small number of colors.
2. Background Art
In general, color images used in color display devices are displayed in terms of RGB color components; 8 bits of memory are allocated to each color component and digitization is thus conducted. Accordingly, in a full-color display which displays the above digitized color image, it is possible to simultaneously display a number of colors corresponding to 24 bits with respect to each picture element, that is to say, to display 2.sup.24 colors so that it is possible to display an image with a natural look.
In contrast, in the world of CD-ROM and CD-I, CAD (Computer Aided Design), CAI (Computer Assisted Instruction), and graphics, it is frequently the case that a color display device which is capable of simultaneously displaying only a limited number of colors selected from among these 2.sup.24 colors, is used. In such a case, the capacity of the image memory corresponding to a picture element is normally 8 bits or fewer, so that the number of colors which can be simultaneously displayed is 2.sup.8 =256.
In addition, if the number of colors is limited to 256 or fewer, it is difficult to display a natural image without deterioration. Therefore there has been a great demand for a device which will make such a display possible.
Furthermore, with regard to the data capacity of the above display device or the like, there has been a great demand for a reduction in the amount of image data and the number of colors of the natural image so that the natural image will not suffer deterioration.
Conventionally, there are known methods which have attempted to solve the problems where a natural image was displayed in terms of a restricted number of colors, while controlling visual degradation by means of a color map display in which a small number of display colors were selected from a large number of colors and displayed.
For example, in the case in which colors were displayed in terms of values for each of the 3 colors R, G, and B, a space in which a 3-dimensional rectangular coordinate system using as coordinates thereof the values for each of R, G, and B, was expressed and used as a color space in such a method. In this color space, each picture element of the color image data was given coordinates corresponding to its RGB values, and an analysis of the distribution of the colors of each picture element included in the color image data was conducted.
Furthermore, a large number of display colors was selected from color regions within the color space for which the distribution of the picture elements of the color image data was large, and a small number of display colors was selected from color regions in which the distribution of the picture elements of the color image data was small. The selected display colors were recorded on a color map, and the closest display color was allocated to each picture element of the color image data as a representative color. Then, by means of writing the color code, recorded as the representative color at the position of each picture element of the image memory into a color map, an approximation of the image was displayed.
Among methods for the selection of representative colors as described above, an example thereof is a method using Otsu's discriminant analysis Shingakuron (THE TRANSACTIONS OF THE IECE OF JAPAN) (D).J63-D, pp. 349-356, 1980-4, and the English abstracts thereof, THE TRANSACTIONS OF THE IECE OF JAPAN, VOL. E63, NO. 4, APRIL 1980, pp. 327-328.
Furthermore, among color spaces, there exist not merely color spaces which express colors by means of combining the three primary colors RGB, but also by means of using uniform color spaces such as the CIELUV color space, CIELAB color space, and the like [recommended by the CIE (Commission Internationale de l'Eclairage)] which take into consideration the visual characteristics of color discrimination by human beings. In addition, it is possible to conduct the above-described discriminatory method of analysis using these color spaces.
Furthermore, a method which utilizes the visual characteristics of color discrimination by human beings, and furthermore applies the Dither method (Journal of the Electronic Imaging Conference, Vol. 18, No. 5 (1989) pp. 293-301; Tajima, Ikeda) has been proposed. However, in this method, consideration is not given to the case in which restricted color display is conducted using a small number of colors, for example, fewer than 100.
In restricted color determination methods utilizing a conventional discriminatory method of analysis, the color distribution was analyzed and a large number of display colors was selected from color regions having a large distribution, while a small number of display colors was selected from color regions having a small distribution, and the closest representative color was allocated to each picture element. In the case in which representative colors were determined and in which portions in the variations of the colors (the values for each of R, G, and B) in each picture element were loose, it was possible to represent the colors of each picture element by means of a small number of representative colors using this method. However, in such a case, pseudo color contouring was often generated. What is meant here by "pseudo color contouring" is a phenomenon in which quantization errors, occurring in portions of the image in which the brightness gradient is loose, have the appearance of contour lines on a map, and thus present a large flaw in the image when displayed (Image Processing Handbook, Image Processing Editing Committee, Shokodo, 1988, p. 191).
For this reason, it was necessary to visually select the portions in which the color variation was loose, to conduct processing of these portions which was separate from that of the other image portions, and for an operator to manually make the corrections at the locations where the pseudo color contouring had occurred after discriminant analysis. Therefore, the process to eliminate pseudo color contouring was extremely burdensome.
Furthermore, in the conventional technology which used the above-described Dither method, a Dithering process was adopted which conducted the appropriate weighting of regions in which the color difference between picture elements in a certain vicinity was small. However, in this Dithering process, only an exchange of colors of each picture element within a predetermined range of colors was conducted, so that while pseudo color contouring was controlled, a diffusion of color occurred with respect to the image as a whole.
Furthermore, even when the discriminatory method of analysis was used in a CIELUV color space or in a CIELAB color space, which take into account the visual characteristics of color discrimination by human beings, an image which approximated a natural image when viewed by the human eye could not be obtained.
Furthermore, among conventional methods and in addition to the non-adaptive methods such as the above-described discriminatory method of analysis and the like, in which an image was created by the selection of a limited amount of display colors independent of the state of the original image, for example, independent of the color distribution thereof, there also existed adaptive methods which selected a restricted number of colors so as to be adapted to the statistical characteristics of the color distribution and the like of the original image.
The above-described adaptive methods were superior to the non-adaptive methods with respect to image quality. However, it was necessary to determine color distribution and the like for all the image data, and it was also necessary to alter the method of statistical processing in accordance with the state of the color distribution so that the processing became complex overall, and the processing period became lengthy.
Accordingly, non-adaptive methods, which maintained a certain amount of image quality with respect to general image data, have been developed to a greater extent than the adaptive methods. The advantages to non-adaptive methods are that they are not particularly selective and that the processing period is short. However, among the natural images which furnish the image data, there are images which have statistical characteristics such as color distribution and the like, which differ extremely based on the content thereof so that the superiority of adaptive methods from the point of view of image quality remains unchallenged.